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Appendix E Ontario Network Environments for Indigenous Health Research and Indigenous Mentorship Network of Ontario’s Indigenizing Health Winter Symposium 2020: Symposium Summary & Event Evaluation Suzanne Stewart, Devon Bowyer, Adriana Gonzalez & Mikaela Gabriel University of Toronto
Event Summary The Ontario Network Environments for Indigenous Health Research (ON NEIHR) and the Indigenous Mentorship Network of Ontario (IMN-ON) held the Indigenizing Health Symposium (Virtual Knowledges Exchange) on December 2nd and 3rd, 2020. Over the two-day event, ON NEIHR team members and IMN-ON students provided researcher and student training pertaining to community-driven Indigenous research processes and procedures, knowledge translation mechanisms, as well as policy development tools that are being conducted in alignment with the ON NEIHR research themes. As COVID-19 mitigation protocols were still in place in December 2020, the Symposium was held virtually via Zoom, allowing a broad range of panelists and attendees from across Turtle Island, Hawai’i, and Australia to participate in the event. Gathering Organizers The Ontario Network Environments for Indigenous Health The ON-NEIHR team comprises Indigenous academics and community partners who specialize in: ● Mental health and research training in the utilization of Indigenous knowledges perspectives; ● Indigenous research ethics, methodologies and community participatory approaches to research; ● The refining of existing mental health models and interventions combined with conducting evaluations based on Indigenous knowledges; ● The development of Indigenous assessment tools and frameworks. Indigenous Mentorship Network of Ontario The Indigenous Mentorship Network of Ontario (IMN-ON) is a five-year health training program committed to supporting and growing a network of Indigenous health scholars. Through training programs and mentorship, students involved in the IMN-ON have the opportunity to partake in Indigenous health and wellbeing research to serve the research needs
